1 citations · 1 across the 10 of their papers we have counts for
10 papers
Leveraging the Power of Large Language Models in Entity Linking via Adaptive Routing and Targeted Reasoning
Yajie Li, Albert Galimov, Mitra Datta Ganapaneni +4
Entity Linking (EL) has traditionally relied on large annotated datasets and extensive model fine-tuning. While recent few-shot methods leverage large language models (LLMs) throug…
DEEPAMBIGQA: Ambiguous Multi-hop Questions for Benchmarking LLM Answer Completeness
Jiabao Ji, Min Li, Priyanshu Kumar +2
Large language models (LLMs) with integrated search tools show strong promise in open-domain question answering (QA), yet they often struggle to produce complete answer set to comp…
AgREE: Agentic Reasoning for Knowledge Graph Completion on Emerging Entities
Ruochen Zhao, Simone Conia, Eric Peng +2
Open-domain Knowledge Graph Completion (KGC) faces significant challenges in an ever-changing world, especially when considering the continual emergence of new entities in daily ne…
Comprehensive Evaluation for a Large Scale Knowledge Graph Question Answering Service
Saloni Potdar, Daniel Lee, Omar Attia +8
Question answering systems for knowledge graph (KGQA), answer factoid questions based on the data in the knowledge graph. KGQA systems are complex because the system has to underst…
KG-TRICK: Unifying Textual and Relational Information Completion of Knowledge for Multilingual Knowledge Graphs
Zelin Zhou, Simone Conia, Daniel Lee +6
Multilingual knowledge graphs (KGs) provide high-quality relational and textual information for various NLP applications, but they are often incomplete, especially in non-English l…
Towards Cross-Cultural Machine Translation with Retrieval-Augmented Generation from Multilingual Knowledge Graphs
Simone Conia, Daniel Lee, Min Li +3
Translating text that contains entity names is a challenging task, as cultural-related references can vary significantly across languages. These variations may also be caused by tr…
Do Large Language Models Have an English Accent? Evaluating and Improving the Naturalness of Multilingual LLMs
Yanzhu Guo, Simone Conia, Zelin Zhou +3
Current Large Language Models (LLMs) are predominantly designed with English as the primary language, and even the few that are multilingual tend to exhibit strong English-centric…
ConvKGYarn: Spinning Configurable and Scalable Conversational Knowledge Graph QA datasets with Large Language Models
Ronak Pradeep, Daniel Lee, Ali Mousavi +7
The rapid advancement of Large Language Models (LLMs) and conversational assistants necessitates dynamic, scalable, and configurable conversational datasets for training and evalua…
AGRaME: Any-Granularity Ranking with Multi-Vector Embeddings
Revanth Gangi Reddy, Omar Attia, Yunyao Li +2
Ranking is a fundamental and popular problem in search. However, existing ranking algorithms usually restrict the granularity of ranking to full passages or require a specific dens…
Entity Disambiguation via Fusion Entity Decoding
Junxiong Wang, Ali Mousavi, Omar Attia +5
Entity disambiguation (ED), which links the mentions of ambiguous entities to their referent entities in a knowledge base, serves as a core component in entity linking (EL). Existi…